deep-research

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Atualizado13 de julho de 2026 às 15:34

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.

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Fonte

TeiNam

TeiNam/kiro-with-harness

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Analistas de pesquisa de mercado e especialistas em marketingNegócios e Operações Financeiras·SOC 13-1161

SKILL.md

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name	deep-research
description	Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
origin	harness
workloads	["research"]

Deep Research

Produce thorough, cited research reports from multiple web sources using firecrawl and exa MCP tools.

When to Activate

User asks to research any topic in depth
Competitive analysis, technology evaluation, or market sizing
Due diligence on companies, investors, or technologies
Any question requiring synthesis from multiple sources
User says "research", "deep dive", "investigate", or "what's the current state of"

MCP Requirements

At least one of:

firecrawl — firecrawl_search, firecrawl_scrape, firecrawl_crawl
exa — web_search_exa, web_search_advanced_exa, crawling_exa

Both together give the best coverage. Configure in your project's MCP settings.

Workflow

Step 1: Understand the Goal

Ask 1-2 quick clarifying questions:

"What's your goal — learning, making a decision, or writing something?"
"Any specific angle or depth you want?"

If the user says "just research it" — skip ahead with reasonable defaults.

Step 2: Plan the Research

Break the topic into 3-5 research sub-questions. Example:

Topic: "Impact of AI on healthcare"
- What are the main AI applications in healthcare today?
- What clinical outcomes have been measured?
- What are the regulatory challenges?
- What companies are leading this space?
- What's the market size and growth trajectory?

Step 3: Execute Multi-Source Search

For EACH sub-question, search using available MCP tools:

With firecrawl:

firecrawl_search(query: "<sub-question keywords>", limit: 8)

With exa:

web_search_exa(query: "<sub-question keywords>", numResults: 8)
web_search_advanced_exa(query: "<keywords>", numResults: 5, startPublishedDate: "2025-01-01")

Search strategy:

Use 2-3 different keyword variations per sub-question
Mix general and news-focused queries
Aim for 15-30 unique sources total
Prioritize: academic, official, reputable news > blogs > forums

Step 4: Deep-Read Key Sources

For the most promising URLs, fetch full content:

With firecrawl:

firecrawl_scrape(url: "<url>")

With exa:

crawling_exa(url: "<url>", tokensNum: 5000)

Read 3-5 key sources in full for depth. Do not rely only on search snippets.

Step 5: Synthesize and Write Report

Structure the report:

# [Topic]: Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*

## Executive Summary
[3-5 sentence overview of key findings]

## 1. [First Major Theme]
[Findings with inline citations]
- Key point ([Source Name](url))
- Supporting data ([Source Name](url))

## 2. [Second Major Theme]
...

## 3. [Third Major Theme]
...

## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]

## Sources
1. [Title](url) — [one-line summary]
2. ...

## Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]

Step 6: Deliver

Short topics: Post the full report in chat
Long reports: Post the executive summary + key takeaways, save full report to a file

Parallel Research with Subagents

For broad topics, use subagents to parallelize:

Launch 3 research agents in parallel:
1. Agent 1: Research sub-questions 1-2
2. Agent 2: Research sub-questions 3-4
3. Agent 3: Research sub-question 5 + cross-cutting themes

Each agent searches, reads sources, and returns findings. The main session synthesizes into the final report.

Quality Rules

Every claim needs a source. No unsourced assertions.
Cross-reference. If only one source says it, flag it as unverified.
Recency matters. Prefer sources from the last 12 months.
Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
No hallucination. If you don't know, say "insufficient data found."
Separate fact from inference. Label estimates, projections, and opinions clearly.

Examples

"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"
"Investigate the competitive landscape for AI code editors"

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name	deep-research
description	Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
origin	harness
workloads	["research"]

Deep Research

Produce thorough, cited research reports from multiple web sources using firecrawl and exa MCP tools.

When to Activate

User asks to research any topic in depth
Competitive analysis, technology evaluation, or market sizing
Due diligence on companies, investors, or technologies
Any question requiring synthesis from multiple sources
User says "research", "deep dive", "investigate", or "what's the current state of"

MCP Requirements

At least one of:

firecrawl — firecrawl_search, firecrawl_scrape, firecrawl_crawl
exa — web_search_exa, web_search_advanced_exa, crawling_exa

Both together give the best coverage. Configure in your project's MCP settings.

Workflow

Step 1: Understand the Goal

Ask 1-2 quick clarifying questions:

"What's your goal — learning, making a decision, or writing something?"
"Any specific angle or depth you want?"

If the user says "just research it" — skip ahead with reasonable defaults.

Step 2: Plan the Research

Break the topic into 3-5 research sub-questions. Example:

Topic: "Impact of AI on healthcare"
- What are the main AI applications in healthcare today?
- What clinical outcomes have been measured?
- What are the regulatory challenges?
- What companies are leading this space?
- What's the market size and growth trajectory?

Step 3: Execute Multi-Source Search

For EACH sub-question, search using available MCP tools:

With firecrawl:

firecrawl_search(query: "<sub-question keywords>", limit: 8)

With exa:

web_search_exa(query: "<sub-question keywords>", numResults: 8)
web_search_advanced_exa(query: "<keywords>", numResults: 5, startPublishedDate: "2025-01-01")

Search strategy:

Use 2-3 different keyword variations per sub-question
Mix general and news-focused queries
Aim for 15-30 unique sources total
Prioritize: academic, official, reputable news > blogs > forums

Step 4: Deep-Read Key Sources

For the most promising URLs, fetch full content:

With firecrawl:

firecrawl_scrape(url: "<url>")

With exa:

crawling_exa(url: "<url>", tokensNum: 5000)

Read 3-5 key sources in full for depth. Do not rely only on search snippets.

Step 5: Synthesize and Write Report

Structure the report:

# [Topic]: Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*

## Executive Summary
[3-5 sentence overview of key findings]

## 1. [First Major Theme]
[Findings with inline citations]
- Key point ([Source Name](url))
- Supporting data ([Source Name](url))

## 2. [Second Major Theme]
...

## 3. [Third Major Theme]
...

## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]

## Sources
1. [Title](url) — [one-line summary]
2. ...

## Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]

Step 6: Deliver

Short topics: Post the full report in chat
Long reports: Post the executive summary + key takeaways, save full report to a file

Parallel Research with Subagents

For broad topics, use subagents to parallelize:

Launch 3 research agents in parallel:
1. Agent 1: Research sub-questions 1-2
2. Agent 2: Research sub-questions 3-4
3. Agent 3: Research sub-question 5 + cross-cutting themes

Each agent searches, reads sources, and returns findings. The main session synthesizes into the final report.

Quality Rules

Every claim needs a source. No unsourced assertions.
Cross-reference. If only one source says it, flag it as unverified.
Recency matters. Prefer sources from the last 12 months.
Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
No hallucination. If you don't know, say "insufficient data found."
Separate fact from inference. Label estimates, projections, and opinions clearly.

Examples

"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"
"Investigate the competitive landscape for AI code editors"